Implementation Of Database Management Systems Research Articles

Lessons Learned from Developing an Industry 4.0 Mobile Process Management System Supported by Artificial Intelligence

Research, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning (artificial intelligence), computational intelligence, and database management systems (DBMS). As nowadays, a numerous of the RDI projects are oriented towards the development of dataintensive solutions, the authors are confident that these lessons will be valuable not only for data engineers, but also for those researchers and practitioners who are dealing with the issues related to building and validating machine learning models, applications of moving averages to high-frequency data streams, and the implementation and deployment of DBMS.

Multicore Processors and Database Systems

Database management systems are necessary for transaction processing and query processing. Today, parallel database systems can be run on multicore platforms. Presented within is an overview of how multicore machines have impacted the design and implementation of database management systems.

Fast decoding algorithms for variable-lengths codes

Data compression has been widely applied in many data processing areas. Compression methods use variable-length codes with the shorter codes assigned to symbols or groups of symbols that appear in the data frequently. There exist many coding algorithms, e.g. Elias-delta codes, Fibonacci codes and other variable-length codes which are often applied to encoding of numbers. Although we often do not consider time consumption of decompression as well as compression algorithms, there are cases where the decompression time is a critical issue. For example, a real-time compression of data structures, applied in the case of the physical implementation of database management systems, follows this issue. In this case, pages of a data structure are decompressed during every reading from a secondary storage into the main memory or items of a page are decompressed during every access to the page. Obviously, efficiency of a decompression algorithm is extremely important. Since fast decoding algorithms were not known until recently, variable-length codes have not been used in the data processing area. In this article, we introduce fast decoding algorithms for Elias-delta, Fibonacci of order 2 as well as Fibonacci of order 3 codes. We provide a theoretical background making these fast algorithms possible. Moreover, we introduce a new code, called the Elias–Fibonacci code, with a lower compression ratio than the Fibonacci of order 3 code for lower numbers; however, this new code provides a faster decoding time than other tested codes. Codes of Elias–Fibonacci are shorter than other compared codes for numbers longer than 26 bits. All these algorithms are suitable in the case of data processing tasks with special emphasis on the decompression time.

RDBAS: A relational database system for non-experienced users

In the last years, the relational approach has developed into a very interesting foundation to the implementation of database management systems oriented towards small computers. This paper deals with a software tool for assisted access to databases using the relational model (RDBAS). A main design goal has been the elaboration of a system whose utilization by unexperienced users requires only a bit of learning effort. Working towards this goal, a non-procedural semi-graphic query language with relational processing capability has been implemented. This language is based on the domain relational calculus and can be used in an interactive way. An interesting feature of this system is the extensibility of its command repertory. Specific purpose new commands can be defined to be used, even by people who are unaware of the query language. Information structures and techniques used in implementation are also discussed.

A database management facility for automatic generation of database managers

A facility is described for the implementation of database management systems having high degrees of horizontal data independence, i.e. independence from chosen logical properties of a database as opposed to vertical independence from storage structures. The facility consists of a high level language for the specification of virtual database managers, a compiler from this language to a pseudomachine language, and an interpreter for the pseudomachine language. It is shown how this facility can be used to produce efficient database management systems with any degree of both horizontal and vertical data independence. Two key features of this tool are the compilation of tailored database managers from individual schemas and multiple levels of optional binding.